Published September 4, 2020 | Version v1
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Meaning maps and saliency models based on deep convolutional neural networks are insensitive to image meaning when predicting human fixations - data

  • 1. Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University
  • 2. University of Tübingen, Center for Integrative Neuroscience, Tübingen, Germany
  • 3. University of Tübingen, Center for Integrative Neuroscience, Tübingen, Germany; Bernstein Center for Computational Neuroscience, Tübingen, Germany

Description

Data from the paper: Meaning maps and saliency models based on deep convolutional neural networks are insensitive to image meaning when predicting human fixations.

Preprint: https://www.biorxiv.org/content/10.1101/840256v1

Marek A. Pedziwiatr
marek.pedziwi@gmail.com
September 2020

 

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data_pedziwiatr_meaning_maps.zip

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Additional details

Related works

Is supplement to
10.5281/zenodo.3490592 (DOI)